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ASAWA: An automatic partition key selection strategy

ASAWA: An automatic partition key selection strategy

引用

15th Asia-Pacific Web Conference on Web Technologies and Applications, APWeb 2013

作者： Wang, Xiaoyan Chen, Jinchuan Du, Xiaoyong School of Information Renmin University of China China School of Information and Electrical Engineering Ludong University China Key Laboratory of Data Engineering and Knowledge Engineering MOE China

ISBN: (纸本)9783642374005

With the rapid increase of data volume, more and more applications have to be implemented in a distributed environment. In order to obtain high performance, we need to carefully divide the whole dataset into multiple partitions and put them into distributed data nodes. During this process, the selection of partition key would greatly affect the overall performance. Nevertheless, there are few works addressing this topic. Most previous projects on data partitioning either utilize a simple strategy, or rely on a commercial database system, to choose partition keys. In this work, we present an automatic partition key selection strategy called ASAWA. It chooses partition keys according to the analysis on both dataset and workload schemas. In this way, intimate tuples, i.e. co-appearing in queries frequently, would be probably put into the same partition. Hence the cross-node joins could be greatly reduced and the system performance could be improved. We conduct a series of experiments over the TPC-H datasets to illustrate the effectiveness of the ASAWA strategy. © 2013 Springer-Verlag.

关键词： data handling

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Classifying tag relevance with relevant positive and negative examples 13

Classifying tag relevance with relevant positive and negativ...

引用

21st ACM International Conference on Multimedia, MM 2013

作者： Li, Xirong Snoek, Cees G. M. Key Lab of Data Engineering and Knowledge Engineering Renmin University of China China Intelligent Systems Lab Amsterdam University of Amsterdam Netherlands

ISBN: (纸本)9781450324045

Image tag relevance estimation aims to automatically deter- mine what people label about images is factually present in the pictorial content. Different from previous works, which either use only positive examples of a given tag or use pos- itive and random negative examples, we argue the impor- Tance of relevant positive and relevant negative examples for tag relevance estimation. We propose a system that se- lects positive and negative examples, deemed most relevant with respect to the given tag from crowd-annotated images. While applying models for many tags could be cumbersome, our system trains efficient ensembles of Support Vector Ma- chines per tag, enabling fast classification. Experiments on two benchmark sets show that the proposed system com- pares favorably against five present day methods. Given extracted visual features, for each image our system can pro- cess up to 3,787 tags per second. The new system is both effective and efficient for tag relevance estimation. Copyright © 2013 ACM.

关键词： Image classification

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Distance-based feature selection from probabilistic data

Distance-based feature selection from probabilistic data

引用

14th International Conference on Web-Age Information Management, WAIM 2013

作者： Zhao, Tingting Pei, Bin Zhao, Suyun Chen, Hong Li, Cuiping Key Lab of Data Engineering and Knowledge Engineering Ministry of Education China Department of Computer Science Renmin University of China China

ISBN: (纸本)9783642385612

Feature selection is a powerful tool of dimension reduction from datasets. In the last decade, more and more researchers have paid attentions on feature selection. Further, some researchers begin to focus on feature selection from probabilistic datasets. However, in the existing method of feature selection from probabilistic data, the distance hidden in probabilistic data is neglected. In this paper, we design a new distance measure to select informative feature from probabilistic databases, in which both the distance and randomness in the data are considered. And then, we propose a feature selection algorithm based on the new distance and develop two accelerative algorithms to boost the computation. Furthermore, we introduce a parameter into the distance to reduce the sensitivity to noise. Finally, the experimental results verify the effectiveness of our algorithms. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Random processes

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Zask: A case study on online collaborative learning

Zask: A case study on online collaborative learning

引用

10th IASTED International Conference on Web-Based Education, WBE 2013

作者： Wang, Xiaoyan Chen, Jinchuan Du, Xiaoyong School of Information Renmin University of China Beijing China School of Information and Electrical Engineering Ludong University Shandong China Key Laboratory of Data Engineering and Knowledge Engineering MOE Beijing China

ISBN: (纸本)9780889869431

Modern educational theories, such as collaborative learning, constructivism and inquiry learning, have achieved many successes in real-world applications. Especially, with the development of information technologies, there have been several online collaborative learning platforms in practice. Unfortunately, as these platforms are either too complicated or too expensive, none of them are suitable for us in the practice of STEM+. Moreover, most of these platforms are in English, while we are using Chinese as our teaching language. Using an online collaborative learning platform (OCLP) named Zask, this paper reported our practice in online collaborative learning on course Introduction to database System. According to the data collected from the first round of our practice, it shows that users' active participations in Zask could benefit for both teaching and learning, and then provide positive effects in education.

关键词： Teaching

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Improved factor analysis algorithm in factor spaces

Improved factor analysis algorithm in factor spaces

引用

2014 International Conference on Informatics, Networking and Intelligent Computing(INIC 2014)

作者： H.D.Wang Y.Shi P.Z.Wang H.T.Liu Key Research Lab on Big Data Mining and Knowledge Management Chinese Academy of SciencesBeijingChina Research Center on Fictitious Economy & Data ScienceChinese Academy of SciencesBeijingChina School of Mathematical SciencesUniversity of Chinese Academy of Sciences Institute of Intelligent Engineering and Mathematics Liaoning Technical University

In order to further improve the velocity and the utilization of information contained in samples,an improved version of the Factor Analysis Algorithm(FAA) in factor spaces is presented in this *** primary algorithm is considered from the whole classes during the selection of the next classified factor,by which a smaller decision domain is generated than that generated by considering from each class,and the deletion of the decision domain is critical in decreasing calculation and increasing the velocity of the ***,based on inheriting the merits of the initial algorithm,the pushing way by each column is changed into that by each class during the selection of the next classified *** change not only decreases the calculation,but also improves the utilization of the sample *** testing results also indicate that the improvement is significant and the testing accuracy rate and velocity are both better than the primary algorithm.

关键词： Factor spaces factor analysis decision domain time complexity

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Efficient querying of correlated uncertain data with cached results

Efficient querying of correlated uncertain data with cached ...

引用

18th International Conference on database Systems for Advanced Applications, DASFAA 2013

作者： Chen, Jinchuan Zhang, Min Xie, Xike Du, Xiaoyong Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China MOE China School of Information Renmin University of China China Department of Computer Science Aalborg University Denmark

ISBN: (纸本)9783642374869

Although there have been many efforts for management of uncertain data, evaluating probabilistic inference queries, a known NP-hard problem, is still a big challenge, especially for querying data with highly correlations. The state-of-art exact algorithms for accelerating the evaluation of inference queries are based on special indices. Besides, with the observation of the existence of many frequent queries, some researchers try to improve efficiency by reusing previously queried results. Indexing depends on the static properties like data distributions, whereas caching is in favor of the dynamic features like query workload. In this paper we propose a new approach for speeding up the evaluation of inference queries by caching frequent results in a junction tree-based hierarchical index. To the best of our knowledge, this is the first effort on utilizing both the static (data) and dynamic (query workload) properties to efficiently evaluate probabilistic inference queries. Moreover, according to our experience, different caching strategies may significantly affect the query performance. Basically a good caching strategy needs to have high cache hit ratio with limited space *** on these considerations, we propose a novel caching approach, called FVEC, and present corresponding algorithms for efficiently querying correlated uncertain data. We further conduct a series of extensive experiments on large uncertain datasets in order to illustrate the effectiveness and efficiency of our proposed approaches. As illustrated by the results, compared with previous solutions, our method could greatly improve the query performance. © Springer-Verlag 2013.

关键词： Efficiency

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Fast SimRank computation over disk-resident graphs

Fast SimRank computation over disk-resident graphs

引用

18th International Conference on database Systems for Advanced Applications, DASFAA 2013

作者： Zhang, Yinglong Li, Cuiping Chen, Hong Sheng, Likun Key Lab of Data Engineering and Knowledge Engineering of Ministry of Education And Department of Computer Science Renmin University of China China JiangXi Agricultural University China

ISBN: (纸本)9783642374494

There are many real-world applications based on similarity between objects, such as clustering, similarity query processing, information retrieval and recommendation systems. SimRank is a promising measure of similarity based on random surfers model. However, the computational complexity of SimRank is high and several optimization techniques have been proposed. In the paper optimization issue of Sim-Rank computation in disk-resident graphs is our primary focus. First we suggest a new approach to compute *** we propose optimization techniques that improve the time cost of the new approach from O (kN2 D2) to O (kNL), where k is the number of iteration, N is the number of nodes, L is the number of edges, and D is the average degree of nodes. Meanwhile, a threshold sieving method is presented to reduce storage and computational cost. On this basis, an external algorithm computing SimRank in disk-resident graphs is introduced. In the experiments, our algorithm outperforms its opponent whose computation complexity also is O (kNL). © Springer-Verlag 2013.

关键词： Search engines

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Towards continuous and passive authentication via touch biometrics: an experimental study on smartphones 14

Towards continuous and passive authentication via touch biom...

引用

Proceedings of the Tenth USENIX Conference on Usable Privacy and Security

作者： Hui Xu Yangfan Zhou Michael R. Lyu Shenzhen Key Laboratory of Rich Media Big Data Analytics and Applications Shenzhen Research Institute The Chinese University of Hong Kong Shenzhen Key Laboratory of Rich Media Big Data Analytics and Applications Shenzhen Research Institute The Chinese University of Hong Kong and MoE Key Laboratory of High Confidence Software Technologies (CUHK Sub-Lab) Shenzhen Key Laboratory of Rich Media Big Data Analytics and Applications Shenzhen Research Institute The Chinese University of Hong Kong and Dept. of Computer Science & Engineering The Chinese University of Hong Kong

ISBN: (纸本)9781931971133

Current smartphones generally cannot continuously authenticate users during runtime. This poses severe security and privacy threats: A malicious user can manipulate the phone if bypassing the screen lock. To solve this problem, our work adopts a continuous and passive authentication mechanism based on a user's touch operations on the touchscreen. Such a mechanism is suitable for smartphones, as it requires no extra hardware or intrusive user interface. We study how to model multiple types of touch data and perform continuous authentication accordingly. As a first attempt, we also investigate the fundamentals of touch operations as biometrics by justifying their distinctiveness and permanence. A one-month experiment is conducted involving over 30 users. Our experiment results verify that touch biometrics can serve as a promising method for continuous and passive authentication.

关键词： smartphone touch biometrics continuous authentication

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Sparse Topic Model for text classification

Sparse Topic Model for text classification

引用

International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Tao Liu Key Laboratory of Data Engineering and Knowledge Engineering (Renmin University of China) MOE

ISBN: (纸本)9781479902590

This paper addresses a new text classification method: Sparse Topic Model, which represents documents by the sparse coding of topics. Topics contain more semantic information than words, so it's more effective for feature representation of documents. Topics are extracted from documents by LDA in an unsupervised way. Based on these topics, sparse coding is applied to discover more high-level representation. We compare the Sparse Topic Model with the traditional methods, such as SVM, and the experimental result show that the proposed method achieves better performance, especially when the number of training examples is limited. The effect of topic number and word number per topic on the performance is also investigated. Due to the unsupervised characteristic of Sparse Topic Model, it's very useful for real application.

关键词： Support vector machines Text categorization Abstracts Semantics Petroleum

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TinyQP: A query processing system in wireless sensor networks

TinyQP: A query processing system in wireless sensor network...

引用

14th International Conference on Web-Age Information Management, WAIM 2013

作者： Mo, Shangfeng Chen, Hong Zhang, Xiaoying Li, Cuiping Key Laboratory of Data Engineering and Knowledge Engineering of MOE Renmin University of China Beijing 100872 China School of Information Renmin University of China Beijing 100872 China Hunan University of Science and Technology Xiangtan 411201 China

ISBN: (纸本)9783642385612

Wireless Sensor Networks (WSNs) can be viewed as a new type of distributed databases. data management technology is one of the core technologies of WSNs. In this demo we show a Query Processing system based on TinyOS in WSNs, which is called TinyQP. TinyQP provides the in-network processing of several complex queries including real time query, historical query, event detection, aggregate query, top-k query, etc. TinyQP displays the network topology in a graphical way. TinyQP allows the user to remotely execute query commands and browse query result. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Query processing

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